Francesco Porpiglia1, Cristian Fiori1, Enrico Checcucci1, Daniele Amparore1, Riccardo Bertolo2. 1. Division of Urology, Department of Oncology, San Luigi Hospital, University of Turin, Orbassano, Turin, Italy. 2. Division of Urology, Department of Oncology, San Luigi Hospital, University of Turin, Orbassano, Turin, Italy. Electronic address: riccardobertolo@hotmail.it.
Abstract
OBJECTIVE: To present our preliminary experience with augmented reality robot-assisted radical prostatectomy (AR-RARP). MATERIALS: From June to August 2017, patients candidate to RARP were enrolled and underwent high-resolution multi-parametric magnetic resonance imaging (1-mm slices) according to dedicated protocol. The obtained three-dimensional (3D) reconstruction was integrated in the robotic console to perform AR-RARP. According to the staging at magnetic resonance imaging or reconstruction, in case of cT2 prostate cancer, intrafascial nerve sparing (NS) was performed: a mark was placed on the prostate capsule to indicate the virtual underlying intraprostatic lesion; in case of cT3, standard NS AR-RARP was scheduled with AR-guided biopsy at the level of suspected extracapsular extension (ECE). Prostate specimens were scanned to assess the 3D model concordance. RESULTS: Sixteen patients underwent intrafascial NS technique (cT2), whereas 14 underwent standard NS+ selective biopsy of suspected ECE (cT3). Final pathology confirmed clinical staging. Positive surgical margins' rate was 30% (no positive surgical margins in pT2). In patients whose intraprostatic lesions were marked, final pathology confirmed lesion location. In patients with suspected ECE, AR-guided selective biopsies confirmed the ECE location, with 11 of 14 biopsies (78%) positive for prostate cancer. Prostate specimens were scanned with finding of a good overlap. The mismatch between 3D reconstruction and scanning ranged from 1 to 5 mm. In 85% of the entire surface, the mismatch was <3 mm. CONCLUSION: In our preliminary experience, AR-RARP seems to be safe and effective. The accuracy of 3D reconstruction seemed to be promising. This technology has still limitations: the virtual models are manually oriented and rigid. Future collaborations with bioengineers will allow overcoming these limitations.
OBJECTIVE: To present our preliminary experience with augmented reality robot-assisted radical prostatectomy (AR-RARP). MATERIALS: From June to August 2017, patients candidate to RARP were enrolled and underwent high-resolution multi-parametric magnetic resonance imaging (1-mm slices) according to dedicated protocol. The obtained three-dimensional (3D) reconstruction was integrated in the robotic console to perform AR-RARP. According to the staging at magnetic resonance imaging or reconstruction, in case of cT2prostate cancer, intrafascial nerve sparing (NS) was performed: a mark was placed on the prostate capsule to indicate the virtual underlying intraprostatic lesion; in case of cT3, standard NS AR-RARP was scheduled with AR-guided biopsy at the level of suspected extracapsular extension (ECE). Prostate specimens were scanned to assess the 3D model concordance. RESULTS: Sixteen patients underwent intrafascial NS technique (cT2), whereas 14 underwent standard NS+ selective biopsy of suspected ECE (cT3). Final pathology confirmed clinical staging. Positive surgical margins' rate was 30% (no positive surgical margins in pT2). In patients whose intraprostatic lesions were marked, final pathology confirmed lesion location. In patients with suspected ECE, AR-guided selective biopsies confirmed the ECE location, with 11 of 14 biopsies (78%) positive for prostate cancer. Prostate specimens were scanned with finding of a good overlap. The mismatch between 3D reconstruction and scanning ranged from 1 to 5 mm. In 85% of the entire surface, the mismatch was <3 mm. CONCLUSION: In our preliminary experience, AR-RARP seems to be safe and effective. The accuracy of 3D reconstruction seemed to be promising. This technology has still limitations: the virtual models are manually oriented and rigid. Future collaborations with bioengineers will allow overcoming these limitations.
Authors: Y Yan; H Z Xia; X S Li; W He; X H Zhu; Z Y Zhang; C L Xiao; Y Q Liu; H Huang; L H He; J Lu Journal: Beijing Da Xue Xue Bao Yi Xue Ban Date: 2019-06-18
Authors: Joshua Makary; Danielle C van Diepen; Ranjan Arianayagam; George McClintock; Jeremy Fallot; Scott Leslie; Ruban Thanigasalam Journal: J Robot Surg Date: 2021-09-04
Authors: Claudia Scherl; Johanna Stratemeier; Celine Karle; Nicole Rotter; Jürgen Hesser; Lena Huber; Andre Dias; Oliver Hoffmann; Philipp Riffel; Stefan O Schoenberg; Angela Schell; Anne Lammert; Annette Affolter; David Männle Journal: Eur Arch Otorhinolaryngol Date: 2020-09-10 Impact factor: 2.503